Doubling down on curation

Earlier this month, Josh Bersin published an interesting analysis that concluded: A New World of Corporate Learning Arrives – And it looks like TV. In it, he points out that emerging platforms for corporate learning are serving up a wide range of content in much the same way that our favorite video providers might – with aggregated resources, playlists, recommendations, personal channels, and more.

It’s great to see that vendors are now devising systems to more seamlessly integrate a wide range of content from multiple providers, including content produced within a given organization. In recent industry conferences, I noted some terrific case studies that demonstrated how organizations are crafting learning pathways consisting of multiple resources and activities that lay out a loose plan to support people who want to work on a specific learning goal. To my way of thinking, these are terrific advancements.

As we move in this direction, it’s important to remind ourselves what curation is actually meant to accomplish. Curation expert Steven Rosenbaum has said, “aggregation without curation is just a big pile of stuff,” and from what I have seen, some of the ways these new platforms serve up resources for learning don’t really go far enough in helping people to find the best resources for their needs in order to truly develop knowledge and skill. It’s just a pile of stuff with little context and priortization.

Effective curation requires tagging, contextualizing, highlighting, making connections, and generating discussion. (I’ve written about this before, here, and here.) These value-added responsibilities go well beyond simply pulling together a list of possible resources and ensuring that they meet your quality criteria. Curation requires human judgement and narration. For your most important projects, it shouldn’t be left entirely to algorithms no matter how useful the algorithms may be. Algorithms filter well, and we can double down on curation from there.

Here are some ideas to consider:

Enrich descriptions with comments that contextualize or highlight key learning points that might be derived from a particular content asset. While we probably don’t need to over-summarize up front, we can point out where the value of the piece lies so that people can look out for it.

Use unique tags (maybe even #hashtags) to direct attention to particular pieces. These can help you support specific projects or ongoing learning efforts.

Use playlist and channel functionality to further refine a list of resources and activities for a specific need. If you’ve contracted with content providers (e.g. Big Think, Harvard Business Review, Lynda.com), a search may generate a fairly long list of potential items. You can help learners by further curating specific pieces for a particular purpose.

Add activities, projects, self-assessments, and reflection/discussion guides to the mix. Reading and watching videos can be important ways to gather information and observe skills – but learning often requires further intellectual processing and taking action. You can give guidance on what to do to study, make meaning, and practice new skills. The more you can do to make these activities context-specific, the more valuable these activities will be.

Help people find your organization’s experts and go-to people. This can be done by allowing people to contribute content and to up-vote the best resources. Encouraging your internal gurus to make recommended playlists can also be a terrific way for people to connect with one another.

Enable asynchronous conversation through comments or discussion functionality. This can be especially useful if a cohort of people are working through a set of goals or learning resources in a defined time frame (e.g. orientation and new hire training, education related to a specific initiative).

In my work on learning environment design, I have long advocated for effective curation of activities and resources to support specific learning goals. It looks like our newest systems may make assembling these resources and packaging them for quick access much easier. But we don’t want to cede design of the learning environment to an algorithm; let’s instead leverage our systems to take curation to the next level, actively assisting people by providing contextualization, recommended activities, and learning advice.